NOCS dataset [1]}: Among existing datasets, this is the closest to the setup here, where instance 3D models are not provided during evaluation. The dataset contains 6 object categories: bottle, bowl, camera, can, laptop, and mug. The training set consists of: (1) 7 real videos containing 3 instances of each category in total, annotated with ground truth poses; and (2) 275K frames of synthetic data generated using 1085 instances from the above 6 categories using a 3D model database ShapeNetCore [2]} with random poses and object combinations in each scene. The testing set has 6 real videos containing 3 different unseen instances within each category, resulting in 18 different object instances and 3,200 frames in total.
